How to approach complexity?

What we’re dealing with

When dealing with issues of design, planning, and organizing, we have to face both complicated and complex problems. A complicated problem is something that might be difficult, but still understandable and predictable. For example, building a watch or a bridge might be very difficult, but still something that we can understand and deal with careful planning. However, many problems are complex, meaning that they are difficult to understand and explain thoroughly. These kinds of problems, also known as messes (Ackoff, 1974) or wicked problems (Rittel & Webber, 1973) require different kinds of approaches and thinking than what we’re normally using in our daily lives.

Where do these problems arise? In an earlier blog post I briefly discussed the concept of SOHO systems (Kay et al, 1999, Kay and Schneider, 1994). SOHO is an acronym for Self-organizing, Holarchic, Open systems. Let’s take a closer look:

  1. Self-organizing means that when the system is pushed from its equilibrium, it might exhibit spontaneous coherent behavior and organization.
  2. Holarchic means that the system is formed up of part-wholes, i.e. holons, and is itself a part-whole. These part-wholes have dynamic interactions both horizontally and vertically across different scales of space and time.
  3. Open means that the system exchanges matter and energy between its environment.

SOHO systems are therefore dynamically relating part-wholes where non-linear feedback loops result in self-organization at different scales in the holarchy. What’s more, when these SOHO systems receive energy from their environment, they develop new structures and processes that make them more effective at receiving energy from their environment.

Ecosystems and human activity systems are prime examples of SOHO systems, both of which exhibit spontaneous coherent behavior and organization, are formed up of part-wholes, and are open. The messes that we face are the result of these dynamic interactions: as we have changed the environment we live in, we have created new and unpredictable changes in ecosystems.

What to do then? When we can’t predict our environment, we need to be able to coevolve with it, and this is where the concept of resiliency comes in.

Design systems for resiliency and learning

First, what is resiliency? From what I’ve learned, there’s at least two views on what resiliency means. The first, engineering approach, says that a resilient system is one that can take on outside shocks and quickly return to equilibrium. The other view, social-ecological resilience, says that a resilient system doesn’t have only one equilibrium, but instead can shift between different states, and learn, change and adapt.

In a wonderful article from 2006, Carl Folke had this to say about social-ecological resilience:

“Adaptive processes that relate to the capacity to tolerate and deal with change emerge out of the system’s self-organization. Furthermore, the dynamics after a disturbance or even a regime shift is crucially dependent on the self-organizing capacity of the complex adaptive system and the self-organizing process draws on temporal and spatial scales above and below the system in focus.”

Without going too much into details, the way I understand Folke is that resilient systems have the capacity to self-organize and create new structures and processes after a disturbance. Moreover, this capacity to self-organize is not a characteristic of one scale in time and space, but is derived from scales both above and below the system, as well as from different scales in time.

I think this point about different temporal and spatial scales is absolutely key here. The way we usually design human systems is by taking a look at one scale or holon at a time. When doing organizational design, you don’t usually start designing the whole that contains the organization. However, based on what Folke said, the capacity to self-organize is not contained at one level of time and space, but draws from all the other scales as well. This is why it’s about social-ecological resiliency, not only human resiliency. Building resiliency in one level will not be enough, and is in fact an illusion.

This also poses a major challenge to planning and design. How to design for resiliency when resiliency is not dependent on any one system? How can we ever build the capacity to self-organize when we can only affect a small part of the whole system at a time?

It would sound that enabling resiliency in our systems requires a paradigm shift at all levels of design. To enable resiliency, we need to change the organizing principles at all scales of social-ecological organization. How exactly are we going to get that done will have to be left for another discussion.


Ackoff, R. (1974). Systems, messes, and interactive planning. Portions of chapters 1 and 2 of Redesigning the future. New York / London. Wiley.

Folke, C. (2006). Resilience: The emergence of a perspective for social–ecological systems analyses. Global Environmental Change. Vol. 16. Pages 253–267.

Kay, J., Regier, H., Boyle, M., Francis, G. (1999). An ecosystem approach for sustainability: addressing the challenge of complexity. Futures. Vol. 31. Pages 721-742.

Rittel, H., Webber, M. (1973). Dilemmas in a general theory of planning. Policy Sciences. Vol 4. Pages 155-169.

Schneider, ED. & Kay, JJ. (1994). Complexity and thermodynamics: towards a new ecology. Futures. Vol. 19. Pages 25-48.




Where to start with systems thinking?

Perfectionism and systems thinking

During the systems thinking 2 course of the Creative Sustainability program in Aalto University, we have encountered various ways of approaching and thinking about systems. Systems thinking as a topic of study is simultaneously both very broad and very deep, and we’ve ended up discussing a wide range of complex issues, including climate change, ecosystem resiliency, and problems in the financial system just to name a few. Having the tools and approaches involved in systems thinking at our disposal has made even the most complex issues at least a bit more tamable.

However, for me, systems thinking has also created an illusion of wholeness in the way people approach complex issues. What I mean is that when we’re talking about complex problems related to human systems by using systems thinking and systems methods, I start to sometimes assume that there must be someone, or some organization that is approaching these issues from a broader perspective. For example, when we were discussing the Viable Systems Model by Stafford Beer in our lecture and applying it to cities, I started to scan in my head for organizations where Viable Systems Model could be applied to cities as a whole. My mind wanted to know the optimal place to be involved in such interventions, as if there was in fact an organization that was trying to solve complex urban problems. Although cities have governments, mayors, and different civic functions, I was searching for an organization that could do a systems design intervention on the whole city scale, including infrastructure, civic services, urban planning etc.

My perfectionist mind wouldn’t therefore be content with approaching cities one aspect at a time, but wanted the perfect approach, and the perfect organization to start with. It would keep asking: how and where could we do an optimal intervention into a complex system or a problem?

Systems thinking ecology

The truth is that there is no one place, time or an organization that would give you a bird’s-eye look at complex situations and allow you to work on the whole system at once. That’s the nature of complex problems: they involve various actors and forces that interact dynamically, meaning that the whole is not controlled by any one organization. That’s why there is no one central location from where to approach complex issues, because if there was, the issues wouldn’t be complex.

Moreover, systems thinkers have developed their ideas in their own unique contexts and backgrounds. The field of systems thinking hasn’t developed from one central place, but is instead a network of loosely coupled scholars and professionals who have built on each other’s work over time. It makes sense then that systems thinking and systems intervention will also have to occur in one context at a time.

So, where to start systems thinking?

Systems thinking needs to begin now, and in the context you’re in. Instead of waiting for the perfect time and place, we must start applying systems thinking whenever and wherever possible. My advice to myself is: don’t try to solve the whole world at once – pick one aspect or a problem situation and start there.

A brief discussion about boundaries and perspectives

Boundary judgments and the Hierarchy theory

In the second session of Systems Thinking 2 course at Aalto University we had an interesting discussion about boundaries and perspectives. One particular remark was made about boundaries, power, and decision-making. In all decision-making settings it’s important to be able to identify who gets to set the boundaries for decision-making. Often, especially in politics, people who have the most power are the ones who get to frame or reframe issues. This is important to understand because the problem-definitions we choose inevitably limit the different alternatives we consider for solving the issue. All kinds of questions are being answered for us when we allow someone else to set our boundaries, including who, what, why, when, and how?

The importance of boundary-setting and framing becomes even more evident when dealing with complex systems, and I dare to claim that most political issues are concerned with complexity. In complex systems, the dynamic interactions between the parts of the system and between the system and its environment make it difficult to predict the outcomes of our actions. It’s anything but easy to decide which interactions to consider in our decisions and which to leave out. So, when we allow others to define the problem space, not only are we placing a lot of faith into their hands, but we also give up much of our decision-making power.

The link between boundary-setting and decision-making is explained well in Hierarchy theory. In Mario Giampietro’s (1994) words:

“It is commonplace to experience a discrepancy in values when assessing the same phenomenon or action from different perspectives. For example, what is good to our taste (assessment on a short timescale) may be harmful to our health (assessment on a longer timescale); the lifestyle of singles is changed after marriage when the same individual becomes part of a larger structure, the family. This pattern is repeated at each enlargement of perspective that brings another hierarchical level into the picture: what is profitable for the family – less taxes – may be harmful to the community to which the family belongs.”

Where are you setting your boundaries?

Where are you setting your boundaries?

This means that decisions at one point in time and scale may affect either negatively or positively the situations in another point in time and/or scale. When we set the boundaries for decision-making at one scale, e.g. the economy, other scales and time-frames might be left out. We could also be neglecting other values and worldviews if we’re not careful.

However, change of boundaries might not lead to changes in perspective. Even when we point out that short-term changes in our economy might in some cases lead to degrading environment (and degrading economy in the long-term), we might still get stuck on the short-term economic perspective. A person might still view that improving the economy creates enough benefits in the short-term to justify lack of consideration for the long-term. In the end, we also have boundaries to our rationality.

Complexity as a matter of perspective

We also had a brief discussion about the nature of complexity. One of our teachers, David Ing, brought up a thought by Timothy F Allen, who had stated that complexity isn’t necessarily an innate characteristic of a system, but rather a matter of perspective. For example, the Apple iPhone might seem complex (or complicated) on the inside, but is relatively simple to use on the outside. A system can therefore be perceived simultaneously as both complex and simple, depending on your perspective.

Let’s take a closer look at the Apple ecosystem. I don’t have an engineering background, but from what I’ve understood, all Apple products taken together basically form an integral system architecture as opposed to a modular one. In a modular system or product architecture the different components of the system have high independence from each other. Thanks to this high independence, components of the system can be relatively easily disassembled and recombined into new configurations, and new product variants can be realized without much difficulty because changes to one component doesn’t lead to changes in other components (Voss & Hsuan, 2011.)

Lego bricks allow modular design.

Lego bricks allow modular design.

The opposite of modular system or product design is an integral design, which I think Apple has chosen for its system. With an integral architecture, components of the system or product are tightly coupled, meaning that modifications to one component require redesigning or re-configuring other components. Apple’s iPhone, Macbooks, the iPod and all other products are all highly integrated to each other. To my understanding Steve Jobs felt very strongly about creating a seamless user experience for Apple products, which he ensured by retaining a strong control on any product modifications. You can’t even change the battery of your iPhone without expert help, let alone start making modifications to the design. Even the chargers to Apple products are different from other manufacturers who mostly use universal chargers.

However, although Apple’s products form an integral system architecture from the perspective of the underlying hardware and software, the Apple Appstore is far from integral. Millions of applications have been created by app-developers all around the world for the Apple iPhone and iPad devices. I think that is an extremely interesting design choice, whether consciously done or not! Ensure efficiency and reliability where it counts (hardware and basic software), but allow variety where people really want it (applications).

So, from one point of view the Apple system is complex, from another simple.


Giampietro, M. (1994). Using hierarchy theory to explore the concept of sustainable development. Futures. Vol. 26, No. 6. Pages 616-625.

Voss, C. & Hsuan, J. (2011). Service science: The opportunity to re-think what we know about service design. In Dermikan, H. (Editor), Spohrer, J. (Editor), Krishna, V. (Editor). The Science of service systems (Pages 231-243.  Springer. New York, USA

Creative Commons Lego Bricks by Benjamin Esham are licensed under CC BY-SA 2.0.

Sense-making in the systems movement – observations of a novice

During the course Systems Thinking 2 at Aalto University we have already had the opportunity to explore different views on how systems thinking can be used in organizational sense-making and design. So far we’ve read and discussed articles about Ackoff’s Interactive Planning, Vicker’s Appreciative Systems, and Haeckel’s Sense-and-Respond organisation. All these views try to bring light on how organizational sense-making can occur, and on how to design systems that can deal with complexity.

What interests me in particular are the different assumptions and broader worldviews that the different approaches hold. The systems movement is a rather complex phenomenon in itself, and for a novice like me, seeing how these approaches relate to each other and the larger context is difficult at first. However, in this blog post I will try to make some sense of the systems movement and explore two major world views that I have recently come across in my readings.

According to the first view, the world is systemic, meaning that it’s formed of interconnected systems. We can objectively observe and design these systems by applying systems thinking principles. This view is based on positivism, spectator theory of knowledge (Dewey, 1929), and functionalism (Zexian & Xuhui, 2010). The second view dismisses the notion that world is essentially systemic and that we can objectively observe it. Instead, this world view builds on social constructionism, the interpretive paradigm, and Dewey’s (1929) experimental theory of knowledge (ibid.) The advocates of the second view argue that the process of inquiry is systemic, and that systems should be viewed ‘as if’ they existed in the real world.

Below is a more detailed discussion of both views, as I have understood them.

The world is systemic – first order (hard) systems thinking

The shift from the doctrine of reductionism and the analytical mode of thought to the doctrine of expansionism and the synthetic mode of thought that took place in the early decades of the 20th century brought with it several lines of inquiry into systems. According to Russell Ackoff (1974), the shift itself began with different scholars in separate fields making a move away from reductionism towards more expansionist thinking. For example, Suzanne Langer discussed the meaning of symbols in the 1940s, with Charles Morris later building on her work to study languages in late 40s and early 50s. From languages the next step was communication by Claude Shannon in 1949 and control and cybernetics by Norbert Wiener in 1948. According to Ackoff (1974), the final “Aha” moment that launched the systems movement was Ludwig von Bertalanffy’s General Systems Theory in the 50s and 60s.

Russell Ackoff.

Russell Ackoff.

These developments lead to the incubation of three distinct, but related systems fields: General Systems Theory, Cybernetics, and Systems Dynamics. All three strands of systems thinking departed from reductionist approaches in that they emphasized the importance of dynamic interactions between the parts of the system and between systems and their environments (Stacey, 2010, 201.) Problem solving did no longer begin by isolating the problem from its environment, but by looking at how the problem is connected to the larger whole that it’s a part of. Synthesis would now precede analysis, instead of the other way around (Ackoff, 1981).

The strands of systems thinking that emerged in these early decades of the systems movement are today called first order systems thinking, or hard systems thinking (Stacey, 2010; Zexian & Xuhui, 2010). Although the proponents of hard systems thinking dismissed the reductionist mode of thought and analytical thinking that formed the basis of the scientific method, hard systems thinking still held many of the beliefs behind reductionist thinking. According to Ralph Stacey (2010), hard systems thinking assumes an objective reality that can be rationally observed by individuals. When it comes to social systems, the social world is essentially assumed to be formed up of systems that have a purpose, and that can be objectively observed and modelled (ibid). The assumptions behind hard systems thinking were conveniently summarized in a 2010 paper by Zexian and Xuhui:

  • System objectively exist in our world and it has a good structure and identified goal.
  • The parts of the system have the same worldviews, values and interests.
  • The system intervener is an outsider of system and is not influenced by the system.
  • Achieving the optimal results is the ultimate goal of problem-solving process (Zexian & Xuhui, 2010, 143.)

According to Zexian and Zuhui (2010), hard systems thinking conforms to positivism in natural science and largely ignores the diverse worldviews, values and interests existing in human organization. Furthermore, hard systems thinking complies with the tradition of epistemology that ignores the relationship between the subject and the object, which Dewey (1929) called the spectator theory of knowledge (ibid.)

In summary, while hard systems thinking moved away from reductionism, i.e., observing and designing parts of a system in isolation, the world view still held on to many of the assumptions behind natural sciences. General Systems Theory, Cybernetics, and Systems Dynamics all assumed that systems could be modelled and understood objectively. Design and sense-making were therefore only a matter of patience and use of rational decision-making tools. Although synthesis would precede analysis, the design of systems could be done using the same scientific rigor that natural scientists used when analyzing natural phenomena.

Emergent behavior. A starling flock near Athens.

Emergent behavior. A starling flock near Athens.


The process of inquiry is systemic – Second order (soft) systems thinking

To recap, General Systems Theory, Cybernetics, and Systems Dynamics all assumed that systems exist as objective phenomena, and that social systems have identifiable goals, structures, and behaviors that we can evaluate and design. In the 1970s and 80s, however, systems thinking scholars began to question these assumptions. Among the most notable critiques were West Churchman (boundaries and moral), Russel Ackoff (Interactive Planning), and Peter Checkland (Soft Systems Methodology), who developed alternative approaches to organizational sense-making and design that involved people. Later the Critical Systems Thinking approach was built on top of the critique from Chruchman, Ackoff, and Checkland (Stacey, 2010.)

Zexian and Xuhui (2010) view Checkland’s Soft Systems Thinking in particular as a major milestone in the systems thinking movement. Checkland critiqued the positivist nature of the earlier systems thinking approaches as well as noting that they don’t consider different human values and worldviews in their analyses. He also dismissed the word ‘system’ altogether and instead employed the term ‘purposeful holon’ to discuss human systems. Below is Checkland’s systems thinking summarized in seven points:

  • System thinking takes seriously the idea of a whole entity which may exhibit properties as a single whole (‘emergence properties’), properties which have no meaning in terms of the parts of the whole
  • To do systems thinking is to set some constructed abstract wholes against the perceived real world in order to learn about it
  • Within system thinking there are two complementary traditions. The ‘hard’ tradition takes the world to be systemic; the ‘soft’ tradition creates the process of enquiry as a system.
  • SSM is a systemic process of enquiry which happens to make use of system models. It thus subsumes the hard approach, which is a special case of it.
  • To make the above clear it would be better to use the word ‘holon’ for the constructed abstract wholes, conceding the word ‘system’ to everyday language and not trying to use it as a technical term
  • SSM uses a particular kind of holon, namely the so-called ‘human activity system’. This is a set of activities so connected as to make a purposeful whole, constructed to meet the requirement of the core system image (emergence properties, layered structure, process of communication and control)
  • In examining real-world situations characterized by purposeful action, there will never be only one relevant holon. It is necessary to create several models of human activity systems and to debate and so learn their relevance to real life (Checkland, 1990, 27).

Checkland therefore states that there is no objective reality that can be observed from the outside, and neither is there only one optimal system (holon) for any situation. If I understood correctly, this is strongly against the first order systems thinking tradition of the 50s and 60s.

In short, the second order systems thinking approaches that were developed in the later decades of the 20th century dismissed the notion of rational observers objectively assessing reality and designing ideal systems based on objective goals. The idea of a system was questioned altogether and replaced by the word ‘holon’. Later, during the 80s and 90s the theories of catastrophe, chaos, and complexity would be added to the already broad spectrum of systems theories and sciences. Exploring the contributions of complexity theories is widely beyond the scope of this blog post, so I will leave the realm of complexity for another discussion.

So, coming back to Vickers’ Appreciative System, Ackoff’s Interactive Planning, and Hacekel’s Sense-and-Respond organisation, I feel it’s already a bit more clear where they stand in the bigger picture. To my knowledge, Ackoff’s critique towards hard systems thinking acted as one of the foundations towards soft systems thinking. Vickers’ Appreciative System method came about as a critique towards the rational decision making models that he saw to have little bearing on how real world works (Burt & Van der Heijden, 2008, 1111). It would therefore seem like a safe bet to say that Vickers also represents second-order systems thinking. I would dare to say that Haeckel too represents second-order systems thinking. In his book ‘Adaptive Enterprise: Creating and Leading Sense-and-Respond Organizations’ (1999), Haeckel builds his idea of a Sense-and-Respond organisation on Learning Organisation theory and Complex Adaptive System (CAS) theory. Learning Organisation theory emerged along with other second-order systems thinking theories, while CAS theory is part of the complexity sciences family.


Ackoff, R. (1974). Systems, messes and interactive planning. Portions of chapters 1 and 2 of Redesigning the Future. New York/London. Wiley, 1974.

Ackoff RL. (1981). Creating the Corporate Future: Plan or Be Planned For. John Wiley and Sons, New York. Pages 16-17.

Burt, G. & van der Heijden, K. (2008). Towards a framework to understand purpose in futures studies: the role of Vickers’ appreciative system. Technological Froecasting & Social Change. Vol 75. Pages 1109-1127.

Checkland, P. (1990). Soft systems methodology in action. Wiley. Chichester, UK.

Dewey, J. (1929). The Quest for uncertainty: a study of the relation of the knowledge and action. Balch & Company. New York, USA.

Haeckel, S. (1999). Adaptive enterprise: creating and leading sense-and-respond organizations. Harvard Business School Press. Boston Massachusetts.

Stacey, R. (2010). Strategic management and organisational dynamics: The challenge of complexity. Pearson Education Limited. Edinburgh Gate, England. Pages 54-55, 201.

Zexian, Y. & Xuhui, Y. (2010). A Revolution in the field of systems thinking – a review of Checkland’s systems thinking. Systems Research and Behavioral Science. Vol 27. Pages 140-155.

Creative Commons Starlings near Athens Nov 2008 by muffin is licensed under CC BY 2.0.

What the heck are SOHOs?

Systems thinking is an important part of our studies in the master’s degree in Creative Sustainability at Aalto University. During a recent course on systems thinking, I ran into an absolutely wonderful and intriguing concept called a SOHO system (1). A SOHO system is a system that is:

  1. Self-Organizing. Self-organizing systems may exhibit spontaneous coherent behavior and organization. This basically means that when an open system, such as a lake or a financial system, is pushed away from its equilibrium state by an influx of energy and material, the system responds with a spontaneous emergence of new, qualitatively different organized behavior and structure. An example of self-organization is the growth of a tree, or the development of an embryo in a mother’s womb.
  2. Holarchic. A holarchic system is formed up of holons. Holons are entities that are simultaenously a whole and a part. A holarchy is therefore a hierarchical system of interconnected part-wholes. These holons are connected with reciprocal relationships and mutual causality – meaning that the interactions between the holons are not linear cause-effect, but non-linear feedback relationships. What all this means is that, instead of having a one-way top-down power relationships as in a traditional view of a hierarchy, holons in each level are affecting other holons in both above and below levels. For example, a forest is a holon, which is consisted of smaller forest areas, lakes, and other ecosystems that are themselves holons. A lake (another holon) then consists of smaller pockets of ecosystems and organisms, that themselves consists of smaller holons… and so on. All the holons and their interactions over time form a holarchy, which extends over time and over different scales.
  3. Open system. Most systems out there are open, including you and me. An open system transmits and receives energy and material to and from its environment. Open systems do have boundaries, but they are not closed or isolated from their context. The opposite of an open system is a closed system. A classic example of a closed system would be the clockwork in a watch.

Self-organizing Holarchic Open systems are all around us. Lakes, forests, societies, social networks, and cities – just to name a few. All of these systems exhibit self-organizing behavior that cascades throughout their hierarchical levels.


A SOHO system in action.

But what really makes the hairs on the back of my neck stand on end is the following idea regarding the energetics of open systems, originally developed by Kay and Schneider (2) , expressed below by Kay et al (1):

“When the input of high quality energy and material pushes the system beyond a critical distance form equilibrium, the open system responds with a spontaneous emergence of new, reconfigured organized behavior that uses the high quality energy to build, organize and maintain its new structure… As more high quality energy is pumped into a system, more organization emerges, in a step-wise way, to dissipate the exergy. Furthermore, these systems tend to get better and better at grabbing resources and utilizing them to build more structure, thus enhancing their dissipating capability.”

If I understand this correctly, this would mean that when a SOHO system receives energy from its environment, it starts to develop new structures and processes that make it more effective at receiving energy from its environment. This creates a positive feedback loop where increasing energy input into the SOHO system increases its capability to receive energy.

A Self-organizing Holarchic Open system. From Kay et al. (1999).

A self-organizing system that uses energy to increase its ability to take energy. From Kay et al. (1999).

For example, when our early ancestors invented tools or developed the ability to cook their food, the community’s ability to grab resources from their environment improved. The increased influx of energy (e.g. cooked food or a surplus of wheat) enabled the community to spend more time improving their tools and techniques, which in turn increased the influx of energy into the community, which again gave the community more time to create new tools and techniques… and so on.

But what does this really mean from practical decision-making point of view? So what if we’re dealing with SOHO systems?

Well, in my view it makes all the difference in the world whether we’re facing systems whose behavior and responses are easy to predict or systems that might have highly unpredictable, or even chaotic behaviors. And we don’t have to look too far to see the consequences of using linear decision-making techniques to non-linear, holarchic and unpredictable systems. Just take a look at the giant garbage patch that’s floating in the Pacific Ocean:

(1) Kay, J., Regier, H., Boyle, M., Francis, G. (1999). An ecosystem approach for sustainability: addressing the challenge of complexity. Futures. Vol. 31. Pages 721-742.

(2) Schneider, ED. & Kay, JJ. (1994). Complexity and thermodynamics: towards a new ecology. Futures. Vol. 19. Pages 25-48.

What Can We Learn From Finnish Anarchists?

The clashes between anarchists and the police during the Finnish independence day have recently been a hot topic of discussion in Finland. A group of anarchists had started a riot on the evening of independence day, which resulted in destroyed public and private property. Destroying small companies’ property has especially been the subject of public outrage. But is there something we can learn from the anarchists?

It is very difficult to understand what the anarchists tried to achieve by breaking other people’s property. One way to look at it is that by breaking stuff the anarchists try to draw attention to issues in our society. What the anarchists probably don’t understand is that the violent actions themselves easily become the center of attention instead of the anarchists’ actual message.

However, shunning the anarchists helps no one either. Pointing fingers and demonizing the rioters only feeds our own egos and makes us feel superior. The reason we make the anarchists the bad guys is because it’s the usual knee-jerk reaction to violence and because it provides a simple cause-effect explanation removing us from any responsibility.

But is there an alternative? If the anarchists aren’t at fault, who is? The reality is that finding fault is irrelevant to begin with. Trying to find someone to blame begins with the false premise that there is in fact someone or something that can be identified as the single cause for our problems. Thus, the alternative to blaming the perpetrators is looking at the issue from a totally different perspective.

Systems thinking

Let me begin by quickly defining the opposite of systems thinking, which I will in this case call linear thinking. Using linear thinking we would conclude that because the anarchists were the ones wrecking places, the problem is in the anarchists. It provides a simple analysis: anarchists break places -> anarchists are the problem. Cause and effect.

Systems thinking would instead begin by trying to view the phenomenon as part of the whole society. According to systems thinking, in order to understand a single event it has to be observed in the context of the larger whole it is part of. In this case, the anarchists’ actions would be explained in the context of the underlying social problems that influence the anarchists’ behavior.

By understanding systems thinking we would realize that the anarchists’ actions do not represent the failing of an individual, but are the end result of some systemic structures in our society. The real issues leading to the events on independence day might have been developing for years, if not decades. Thus, issuing blame on individuals is useless, if not dangerous because it prevents us from understanding the real causes.

I am not saying that individuals shouldn’t be held accountable for their actions. Free will still exists and individuals need to take responsibility for their behavior.

What I am saying is that we need to start talking about the real issues rather than pointing fingers.


Creative Commons Skate and riots by Sergio is licensed under CC BY 2.0

Events, Behavior, Structure

Why is it sometimes so incredibly difficult to change one’s behavior? Why do some events and outcomes seem to repeat themselves over and over regardless of our best attempts to change them? And why do some countries and areas have more crime, poverty and other societal issues than others? If you have read my older posts, you might agree with me that crime and poverty are not first and foremost the failing of an individual, but the results of system level problems. In this blog post I want to introduce an effective systems thinking approach for identifying the root causes of systemic problems.

The tip of the iceberg

We humans tend to become pre-occupied with reacting to events that require our immediate attention. I’m guessing this is partly because of our ancestors’ survival instincts. Our primitive ancestors were forced to react immediately – to fight or flight – to threats in their environment or perish. Being armed with the same instincts, our emotions guide us to quickly react to arising problems. This is a necessary skill if you want to survive in the nature, but the bias towards the immediate sometimes prevents us from understanding the real reasons behind certain problems. The problem is that our instincts are not always so good at recognizing which problems are truly important and which ones are merely urgent. This hinders our ability to see the bigger picture and to recognize slowly evolving changes that affect us.

With increased complexity, the issues we deal with as individuals and as a society require much deeper understanding than the problems our ancestors had to face. Quick fixes never work because the underlying root causes are left untreated. To make matters worse, our ancestors’ survival instincts cause us to over-react emotionally even when the problem at hand would require us to keep our cool. News and other media amplify this problem by giving emphasis on bad news. The media also tends to focus on reporting one-time events, celebrity news and entertainment, which distorts people’s world view and hides the real issues.

The over-emphasis on one-time events is dangerous. It prevents us from understanding the real problems behind issues and creates a quick-fix culture. If the economy is down, we blame the government. When there is disease, we treat the symptoms. Where there is poverty, we give money to the poor or blame the individual. What we need to understand is that events and the perceived state of affairs are the end results of complex processes instead of simple cause-effect relationships.  They are only the tip of an iceberg.

What is hiding under water?

How can we re-orient ourselves to understand the whole iceberg? Peter Senge, a well-known organizational learning expert and a systems thinker, tackles the issue in his book The Fifth Discipline. According to Senge, there are always multiple levels of explanation to a complex situation. Understanding the different levels of complexity can help us find the root causes of problems and prevents us from jumping into conclusions about a situation. Take a look:


I recently read a news piece about a Finnish nickel mine company, situated in my home region Kainuu. The article stated that the company had failed the expectations of its shareholders and the people in the region. The article also described comments from the shareholders, many of whom were small investors and had invested large portions of their savings on the company’s stock. Most of the shareholders interviewed in the article complained that the company and the CEO had failed them, with some stating that the company had outright fooled them out of their money.

The shareholder’s view represented in the article is a demonstration of an event-level explanation. It provides a simple cause-effect analysis of the situation where the mining company and its leadership are seen as the cause for the shareholders’ problems. Losing money is seen to be the outcome of the company’s bad managing. It is extremely tempting to find simple causes behind problems because it protects our own ego and presents the path of least resistance. Unfortunately event explanations are usually based on quickly made conclusions and generalizations that tell more about our own prejudices and fears than about reality.

Patterns of behavior

The second level of explanation already goes much deeper than event explanations. Rather than fixating on single events, we can attempt to find patterns of behavior and long-term trends that affect our lives and our society. In the nickel mine example we might find that small investors are often financially uneducated, which is why they are more easily tempted to place their savings into single investments. The problem definition is now fundamentally different from the previous one. Instead of perceiving the company’s management as the root cause, we would accept that companies sometimes do fail and conclude that the real problem is our inability to take this into account when investing.

Here’s another example: suppose the occurrences of type two diabetes in a nation are rising. A reactionary response, based on an event level explanation would be to prescribe medicine for the disease. Understanding patterns of behavior would, however, enable us to see that obesity is the real problem, which would prompt a very different solution. Instead of treating the symptom, i.e. diabetes, we would try to influence people’s behavior in some way to reduce obesity.

Systemic structure

The third level of explanation is concerned with systemic structures. It essentially means identifying and understanding the structures that push us to behave in a certain way. Structures that affect our behavior include but are not restricted to:

  • physical structures, e.g. transportation infrastructure, architecture
  • cultural & social structures, e.g. social norms, social classes
  • legal & institutional structures, e.g. laws, organizations, regimes
  • economic structures, e.g. financial systems

All the above structures affect our behavior in many ways and are an extremely important to understand. A complex problem must be addressed in the context of the larger whole it is a part of. In the  nickel mine case we could try to identify structures in the financial and cultural systems that drive people to take too much risk. Perhaps there are structures in place that cause us to look for short-term gain or to be impatient with our investments? We could also ask questions about our current economic system: are there some key areas in our system that drive harmful behavior in publicly owned companies? Are we using the right metrics to measure companies’ performance and the economic system as a whole? These kinds of questions help us look at the bigger picture and identify the deeper  causes of problems.

Mental models

The final and the most important level of explanation deals with our mental models. Our human systems are ultimately a reflection our own thinking and the prevailing mental models in our society. Systemic structures are also an outcome – an artefact of sorts – of human thinking. Observing different cultures reveals differences in mental models. Time, for example is viewed very differently in different parts of the world, which has a major impact on the way people behave and plan their lives.

Because mental models influence everything we do it is the ultimate leverage when pursuing change. Therefore, instead of over-emphasizing the significance of one time events, we should observe our thinking habits and see how they affect systemic structures and patterns of behavior.

How to use the different levels of explanation?

Here are some suggestions for using Senge’s framework:

  • Next time you watch news, think about the behavior and the structures that might have caused the events being discussed.
  • If you find yourself blaming someone or something for a problem in your life, try to think of ways you could have prevented it with your own behavior. What could have been done differently? Try to find a structure that might have caused any potential un-beneficial behavior.
  • Observe your own thinking: can you identify strong mental models or mind-sets? If you can identify your mental models, try questioning them. Are they true? Why or why not? You can also try to think of ways your mental models are affecting your behavior.

Stock and Flow Pt.1 – Introduction and Intuition

So far I have done my best to provide some intuition about systems thinking and why it might be important to you (while sharpening my own thinking as well). Through the few examples, we now understand that a system is the product of the interactions of its parts and that the structure of the system causes its behavior. We also know to look for circles of causality instead of fixating on one time events. I will now introduce another very important concept that will further enhance our basic understanding of the systems we deal with in our every day lives. It will also allow us to develop some real systems thinking skills and habits.

Stock and flow

If you let water run freely into a bathtub with the drain plugged up, the water level will start to rise steadily until it fills the bathtub. You have built a stock, in this case a small body of water, into the bathtub. By unplugging the drain in the bathtub, you can increase the outflow of water from the tub, thus decreasing the stock of water. If you had both the faucet on and the drain unplugged, you would have two flows of water, with one flowing into and the other out of the bathtub. Similarly, if you refill your refrigerator without using any of the food, you will have accumulated a stock of food. When you begin consuming the food, you increase the outflow from the stock, thus changing the size of the stock. In systems thinking terms, you have created a system of stock and flow.

Stock and flow systems are a fundamental systems thinking concept that are used when doing a system analysis. It is important to understand stock and flow systems because it helps us understand the various systems that affect our lives. A stock and flow system is usually illustrated with a following kind of image:

stock and flow

Usually flows are represented with an arrow similar to the one in the picture, with stocks depicted as squares. The small thingy on the arrow represents a mechanism which can influence the flow into the stock. In the bathtub example the mechanism would be the faucet, but it can also be something immaterial, e.g. laws or other restrictions. The small cloud at the other end of the arrow represents a source, which is ignored for the purposes of narrowing down the analysis.

The world is full of stock and flow systems that affect our lives. Airports, train stations, and busy intersections are good examples of physical stock and flow systems. Fisheries are important stock and flow systems found in nature, and are often mentioned when talking about sustainability issues. Many industrial companies can be modeled as relatively simple stock and flow systems, with a flow of supplies coming in for the manufacturing process and a flow of finished goods coming out. Similarly schools, hospitals, banks, grocery stores, and even complex political and social systems can be modeled as stock and flow systems.

But why are stocks and flows so important? What does it matter if we know about them or not?

Well, think about the way we usually approach stock and flow systems in our daily lives.We tend to be somewhat ignorant about our behavior towards stocks and flows: how many times have you ended up depleting your stock of food before going to the grocery shop? And how many times have you been stuck in traffic because you did not leave early enough to avoid it? There must have also been times when you have run out of money before the end of the month, having to either use up savings or eat noodles to get by before next pay check. We all tend to have difficulties balancing the stocks and flows of our every day lives.

But since we have difficulties dealing with these very simple systems, what about more complex and more important systems? We often treat natural systems the same way we are treating our refrigerator. We deplete fisheries and acidify the oceans. The rainforests are being hacked away at an alarming rate and we have also been extremely efficient at killing off numerous species of animals. Furthermore, we don’t seem to fully understand the workings of our own man-made systems either! This was demonstrated in the 2008 financial crisis, whose aftermath we are still living today.

If we want to live in a sustainable way and make sure we have a place in this world, we need to develop our understanding of the systems we deal with every day. Understanding stock and flow is only one part of the equation, but it is a very important part. In order to better understand stock and flow, I will next time talk about balancing and reinforcing feedback!

Practice suggestion: Try to look for stock and flow systems in your surroundings. Try to identify the different flows and the stocks they are flowing into and out of. Notice: the flows and the stocks can be either tangible (e.g. water, people, food) or intangible (electronic currency, ideas, political opinions).

Systems Thinking Example 3: The Faucet

In the previous two examples I have introduced two basic systems thinking principles. The automobile example from Russell Ackoff demonstrated that a system is not the sum of its part but the product of their interactions. The second example was from Donella Meadows, and the lesson was that the behavior of the system can only be changed by changing the system itself. In this blog post I will briefly touch upon how to think about any situation using systems thinking with an example from Peter Senge’s book The Fifth Discipline.

Let’s begin again with a thought experiment. Imagine that you’re thirsty and decide to have glass of water. You take a glass, go to a water tap and fill the glass in order to have a drink. If we were thinking linearly, we would see a simple cause and effect relationship: you filling a glass of water. However, the situation looks different from a systems point of view. (The below pictures are from Senge’s book The Fifth Discipline.)


When you’re filling the glass with water, there are actually several things happening at the same time. You have a desired water level in mind, so while the water is pouring into the glass, you’re monitoring the ‘gap’ between the current water level and your goal. As the water level rises, you are adjusting the faucet with your hand and finally closing it when the water has reached the desired level. You are, in fact, engaged in a system that has five variables:

  1. the desired water level
  2. the current water level
  3. the gap between the two
  4. the faucet position and
  5. the water flow

Faucet 2

The above picture illustrates how the different elements of the system influence one another. You can begin reading the picture from anywhere. An arrow indicates the direction of influence. Desired water level influences the perceived gap, which influences the faucet position, which again has an influence on the water flow. When the water flow changes, it in turn has an effect on the current water level, which finally influences the perceived gap.

This is how systems thinkers view situations, problems and the world in general. Instead of one time events and simple cause-effect relationships, they see circles of causality. This thinking can be applied to practically every major problem out there.

Think about terrorism for instance: most of the time we only pay attention to the one time incidents and terrorist attacks we see in the news. What we don’t know is what has been influencing the terrorists in a way that causes them to take violent action. With only superficial knowledge about the reasons behind terrorism, we then respond in fear and anger, which often only increases the terrorists’ conviction.

Not all situations work this way though. If you were to kick a ball, the ball would simply bounce away. Here a simple cause-effect analysis would be sufficient and the event could be explained with physics. However, if you were to kick a dog, the poor creature would react in some way. It might run away, but it could also attack you. You are influencing the dog’s behavior by kicking it and in return the dog will influence your behavior by attacking you. If I were to walk in a room where I only see the dog attacking you, I might easily jump into conclusions about the dog too quickly. This is how we humans perceive the world most of the time, which is why our problem definitions are often so badly off the mark.

The Principle: Instead of seeing one time events, look for circles of causality.

Other implications of this principle:

  • Next time when someone is angry at you, try to look for ways you might have influenced his or her behavior.
  • In the news you see only one time events and the end results of some larger phenomenon. Instead of talking about the event itself, try to think about what kind of circles of causality might have caused the event.
  • In an arms race between nations there is no one country or individual to blame. It is the result of all the countries influencing one another.

Ps. Take a look at this short introductory video for systems thinking:

Creative Commons Dripping Tap by Fred Dawson is licensed under CC BY 2.0.

Systems Thinking Example 2: Slinky

In her book Thinking in Systems, Donella Meadows tells how she would often bring a slinky to her classes in order to teach her students systems thinking. What exactly can we learn about systems thinking from a slinky?

Suppose you’re holding a slinky in one upturned hand with the other hand under the slinky. Holding the slinky with one hand you pull the other hand away and let slinky loose. As you’d imagine, the lower end of slinky will bounce up and down in air, with the upper end suspended in your fingers. The question is: what made slinky bounce up and down?

The first answer that might cross your mind is that your hand was the cause. By removing your hand below slinky you let it loose which made it bounce. However, it’s clear that you would not get the same reaction by holding a book, a hammer, or anything else other than slinky in your hand. Slinky bounces up and down because of some inherent characteristic within slinky itself. If that’s the case, what does this actually teach us about systems thinking?

In slinky’s case its easy to understand that slinky is a physical system whose behavior is fundamentally dependant upon two things: 1. the characteristics of the system, 2. outside forces affecting the system. If you manipulate slinky in different ways you would get different behaviors, but the behaviors would always be closely related to slinky’s internal qualities.

But why is this important? Well, just think about how governments, politicians, organizations and institutions usually approach problem solving. Drug problems are solved by putting addicts into prison, type two diabetes is taken care of by prescribing medicine, and poor economic growth is resolved by subsidizing badly performing industries. Different countries have their own bad examples, but the thinking behind the issues is often the same. We as humans tend to often focus only on changing the way we manipulate a system, instead of changing the system itself!

With simple physical systems we know how to make system change possible: you would not use slinky to hammer a nail, you’d use a hammer. However, with more complex systems, such as schools systems or cities, we sometimes forget that the behavior we witness is the result of the system acting the way it’s design to act. If the end result of a system is drug addicts and population suffering from diabetes, then the system has been designed to produce these results. Instead governments and organizations often find blame in some outside forces. They try to fix the issue by starting initiatives and programs rather than changing the system itself. In the US the government appears to often declare war against societal issues, effectively preventing any real change from happening. In Finland, our government attempts to get students to graduate faster by placing restrictions on maximum study years, which is another demonstration of linear thinking.

The principle: The system itself often causes its own behavior. In order to change the behavior, change the system.

Other implications of this principle:

  • A failing industry is not always the result of bad policy or leadership. Creative destruction is part of the continuous cycle of innovation that drives our economies (a self-renewing system)
  • Type two diabetes and heart problems are not the failing of an individual. We have encouraged the development of industries that produce foods that are cheap and unhealthy. We have also made easy access to these foods possible.
  • Long times of graduation in Finland are not because students are lazy. Our education system encourages students to postpone graduation.


Creative Commons NYC – MoMA: Philip Johnson Architecture and Design Galleries – Slinky by Wally Gobetz is licensed under CC BY 2.0.